Paper Citation Record · LEDGER

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction

As of 14 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2509.01016.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.01016 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:02:25.700489Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact2
verified fuzzy2
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2050d73d-75ec-4ceb-a539-ec334a6283e0 · outbound

This paper cites Program Synthesis with Large Language Models.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Program Synthesis with Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.389421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c231f64-c131-4801-ae8f-fb18e7044319 · outbound

This paper cites On the Measure of Intelligence.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction On the Measure of Intelligence

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.654585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5cfcd01-67d7-40f2-aaba-a88bad32e4fd · outbound

This paper cites Fast and flexible: Human program induction in abstract reasoning tasks.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Fast and flexible: Human program induction in abstract reasoning tasks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.664657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87485ab1-cc41-46b0-ab1c-bf5f46ccf7df · outbound

This paper cites Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:02:25.813975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 65e5a845-0c26-4d09-afe7-81e587a3d83c · outbound

This paper cites Neuro-Symbolic Program Synthesis.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Neuro-Symbolic Program Synthesis

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.677097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b96d003-fa18-4c0f-86b1-87b6f26ffb05 · outbound

This paper cites Synchromesh: Reliable code generation from pre-trained language models.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Synchromesh: Reliable code generation from pre-trained language models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.683116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8abaa7d9-45a1-42d3-b576-2f6aa39dcd9e · outbound

This paper cites Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.686347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 124961d5-7bfa-4f46-8737-c33680050746 · outbound

This paper cites LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.692131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cb7339b-2974-4e70-b30f-3ce39cd11387 · outbound

This paper cites an unresolved cited work.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-05T13:02:25.913633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f3c856b5-d319-4bf8-b45d-ce4a8df13af2 · outbound

This paper cites Human learners reach 0.521, slightly higher than hypothesis search at 0.487.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Human learners reach 0.521, slightly higher than hypothesis search at 0.487

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:02:25.895429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a0057f78-198d-4e9c-9583-be53aceda6ae · outbound

This paper cites [2024], where Codex was evaluated under Direct Program Generation.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction [2024], where Codex was evaluated under Direct Program Generation

Reference 1000

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:02:25.904676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 035562de-61bb-4dc9-a17f-ee36bdc0f4aa · outbound

This paper cites Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning

Reference 1868

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:02:25.771453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 76490900-134b-43c7-a68a-89e6983d81df · outbound

This paper cites Symbolic Regression with a Learned Concept Library.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Symbolic Regression with a Learned Concept Library

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.661491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c048c413-1338-4c46-8ad1-e97401805e32 · outbound

This paper cites Large Language Models Are Not Strong Abstract Reasoners.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Large Language Models Are Not Strong Abstract Reasoners

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.658020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e1a1121-bf13-4722-9e00-731defa32c84 · outbound

This paper cites Hypothesis Search: Inductive Reasoning with Language Models.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Hypothesis Search: Inductive Reasoning with Language Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.689262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98ebe19d-da34-4ac3-bed3-34796327e04c · outbound

This paper cites Large Language Models as General Pattern Machines.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Large Language Models as General Pattern Machines

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.674181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 268f1ab2-9b50-4e92-9afc-a18a717e6f6f · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.632997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4d4a9fd-1748-4182-a042-072b526c0b6c · outbound

This paper cites Language Models are Few-Shot Learners.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Language Models are Few-Shot Learners

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.506651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66107e61-f80f-4e80-9114-6551f7d88f67 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction Evaluating Large Language Models Trained on Code

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.650984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9d58c0d-fa06-42ac-8b97-83ff83a21afb · outbound

This paper cites The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision.

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T13:02:25.671084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.